Prediction of nitrogen excretion in buffalo production systems using dietary and animal variables

Abstract

Presently, there are no models for predicting nitrogen excretion (NE) in buffaloes, which are required for preparation of inventory of NE. Thus, this study aimed to develop statistical models to predict NE from animal and dietary characteristic variables. A dataset of 481 treatment means from 143 publications was constructed, which contained at least NE and nitrogen intake (NI) data. Simple and multiple regression models were developed using the datasets containing all animals, growing or lactating buffaloes. The models that predicted faecal NE (g/d) with high precision and accuracy were faecal NE (g/d) = 13.4 (±3.30) + body weight (BW; kg) × 0.023 (±0.0083) – crude protein (CP) content of diet (g/kg) × 0.080 (±0.0211) + NI (g/d) × 0.288 (±0.0148) [RMSPE = 26.5%, with 98% of mean square prediction error (MSPE) being random error; R2 = 0.77] for all animals, and faecal NE (g/d) = 17.7 (±4.04) + BW (kg) × 0.033 (±0.0167) – ADG (kg/d) × 10.2 (±2.99) – CP (g/kg) × 0.052 (±0.026) + NI (g/d) × 0.231 (±0.0324) [RMSPE = 27.9%, with 96.4% of MSPE being random error; R2 = 0.49] for growing animals only. The best predicted regression equations for urinary NE (g/d) = −10.8 (±5.15) + BW (kg) × 0.019 (±0.0129) + CP (g/kg) × 0.056 (±0.0298) + NI (g/d) × 0.334 (±0.0206) [RMSPE = 45.5%, with 90% of MSPE from random error; R2 = 0.65] for the dataset containing all animals; and urinary NE (g/d) = 4.23 (±3.89) – BW (kg) × 0.039 (±0.0188) – ADG (kg/d) × 13.2 (±4.51) + NI (g/d) × 0.421 (±0.0313) [RMSPE = 33.2%, with 92.4% of MSPE accounting random error; R2 = 0.61] for only growing animals. In lactating buffaloes only, no models containing milk yield as a predictor were reliable for predicting NE perhaps due to paucity of studies included in the dataset. Prediction models for urinary NE had usually greater RMSPE compared with the models for faecal NE. The equations developed in the present study were found suitable for estimation of NE factors from different categories of buffaloes with different BW, ADG and feeding conditions. The models developed in the present study would be useful for preparation of global inventory of NE and separate estimation of urinary and faecal NE in buffaloes.